Ending day prediction of nCoV2019
12/08/2020
source('./predict.R')
## [1] "2020-08-11"
## country cum_confirm cum_heal cum_dead inc_r d_rate d_pm
## 1 United States 5253765 2717257 166273 1.01 3.16 502
## 2 Brazil 3057470 2163812 101857 0.72 3.33 479
## 3 Mexico 485836 327993 53003 1.16 10.91 411
## 4 United Kingdom 311641 1918 46526 0.26 14.93 685
## 5 India 2287511 1598529 45550 2.75 1.99 33
## 6 Italy 250825 202248 35209 0.10 14.04 582
## 7 France 202775 82836 30340 2.45 14.96 465
## 8 Spain 370060 196958 28576 2.38 7.72 611
## 9 Peru 483133 329404 21276 1.07 4.40 645
## 10 Iran 331189 288620 18800 0.71 5.68 224
## 11 Russia 897599 703175 15131 0.55 1.69 104
## 12 Colombia 397623 221485 13154 2.62 3.31 259
## 13 South Africa 563598 417200 10621 0.67 1.88 179
## 14 Chile 375044 347342 10139 0.53 2.70 530
## 15 Belgium 74620 17792 9879 0.63 13.24 852
## 16 Germany 218974 202187 9365 0.45 4.28 112
## 17 Canada 120132 106355 8987 0.57 7.48 238
## 18 Netherlands 59973 322 6159 1.32 10.27 359
## 19 Pakistan 285191 261246 6112 0.19 2.14 28
## 20 Ecuador 94701 78608 5932 0.26 6.26 336
## 21 Turkey 241997 224970 5858 0.50 2.42 69
## 22 Indonesia 128776 83710 5824 1.33 4.52 21
## 23 Sweden 83126 4971 5770 0.98 6.94 571
## 24 Iraq 156995 112102 5531 2.21 3.52 138
## 25 Egypt 95666 53779 5035 0.18 5.26 49
## 26 Argentina 253868 174974 4764 2.99 1.88 105
## 27 China 89416 82873 4699 0.08 5.26 3
## 28 Bolivia 91635 30823 3712 1.82 4.05 318
## 29 Bangladesh 263503 151972 3471 1.15 1.32 21
## 30 Saudi Arabia 291468 255118 3233 0.52 1.11 93
## 31 Romania 63762 30585 2764 1.94 4.33 144
## 32 Philippines 139538 68432 2312 2.12 1.66 21
## 33 Guatemala 56987 45589 2222 0.67 3.90 124
## 34 Switzerland 36895 32400 1990 0.51 5.39 230
## 35 Ukraine 83115 44934 1951 1.41 2.35 45
## 36 Poland 52961 37150 1821 1.05 3.44 48
## 37 Ireland 26768 23364 1772 0.21 6.62 359
## 38 Portugal 52825 38600 1759 0.30 3.33 173
## 39 Panama 75394 49510 1664 1.21 2.21 386
## 40 Honduras 47872 6649 1506 0.88 3.15 152
## 41 Kyrgyzstan 40455 32734 1478 0.92 3.65 227
## 42 Afghanistan 37269 26415 1344 0.29 3.61 35
## 43 Dominican Republic 80499 44910 1328 0.96 1.65 122
## 44 Algeria 35712 24920 1312 1.41 3.67 30
## 45 Kazakhstan 100164 73702 1269 0.73 1.27 68
## 46 Japan 50444 33975 1058 1.40 2.10 8
## 47 Nigeria 46867 33346 950 0.62 2.03 5
## 48 Moldova 27841 19300 850 0.65 3.05 211
## 49 Armenia 40593 33157 803 0.40 1.98 271
## 50 Sudan 12033 6282 786 0.64 6.53 18
## 51 Austria 22245 20123 723 0.63 3.25 80
## 52 Serbia 28497 18965 652 0.83 2.29 75
## 53 Denmark 15135 13154 620 2.55 4.10 107
## 54 Israel 85354 60019 619 2.17 0.73 72
## 55 Belarus 69005 65219 592 0.08 0.86 63
## 56 El Salvador 21269 9875 570 1.90 2.68 88
## 57 Oman 82050 76720 533 0.32 0.65 104
## 58 Republika Severna Makedonija 12083 8248 529 2.06 4.38 NA
## 59 Morocco 34063 24524 516 2.49 1.51 14
## 60 Azerbaijan 33731 30856 495 0.25 1.47 49
## 61 Kuwait 73068 64759 486 0.92 0.67 114
## 62 Bulgaria 13512 7980 459 0.87 3.40 66
## 63 Bosnia and Herzegovina 14708 8411 447 7.46 3.04 136
## 64 Kenya 27425 13867 438 1.85 1.60 8
## 65 Ethiopia 23591 10411 420 3.39 1.78 4
## 66 Cameroon 18042 15320 395 0.00 2.19 15
## 67 Czech Republic 18494 12983 390 0.76 2.11 36
## 68 United Arab Emirates 62966 56961 358 0.71 0.57 36
## 69 Australia 21713 12144 331 1.43 1.52 13
## 70 South Korea 14660 13729 305 0.23 2.08 6
## 71 Puerto Rico 22821 0 279 0.00 1.22 98
## 72 Costa Rica 23872 7823 244 2.52 1.02 48
## 73 Senegal 11380 7449 238 0.60 2.09 14
## 74 Venezuela 26800 16930 229 3.86 0.85 8
## 75 Ghana 41212 38727 215 0.51 0.52 7
## 76 Uzbekistan 31747 23704 204 2.19 0.64 6
## 77 Qatar 113262 109993 188 0.00 0.17 65
## 78 Bahrain 44397 41209 165 0.88 0.37 97
## 79 Madagascar 13317 11276 152 0.87 1.14 5
## 80 Côte d'Ivoire 16798 13052 105 0.50 0.63 4
## 81 Palestinian Territory 14875 8181 103 2.52 0.69 NA
## 82 Nepal 23948 16664 83 2.74 0.35 3
## 83 Singapore 55353 49609 27 0.11 0.05 5
## [1] "Pakistan leading 1 cum_confirm == 0 trimed"
## [1] "Provinces added more than 0 cases in last 1-day:"
## time country province cum_confirm cum_heal cum_dead added
## 1 2020-08-11 China Hong Kong 4181 3052 58 33
## 2 2020-08-11 China Xinjiang 866 337 3 13
## 3 2020-08-11 China Shaanxi 340 322 3 9
## 4 2020-08-11 China Shanghai 794 737 7 8
## 5 2020-08-11 China Shandong 816 788 7 6
## 6 2020-08-11 China Guangdong 1699 1672 8 3
## 7 2020-08-11 China Hebei 350 343 6 1
## 8 2020-08-11 China Heilongjiang 948 934 13 1
## 9 2020-08-11 China Zhejiang 1274 1268 1 1